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Freelance Data Engineering Jobs in California (NOW HIRING)

E2B

Technical Copywriter

San Francisco, CA · On-site

$150K - $200K/yr

... engineers and the codebase; produce customer case studies; and edit work from specialist freelancers. Every piece should be technically credible, easy to understand, and structured so we can measure ...

SysMind Tech

Datawarehouse TEST LEAD

Los Angeles, CA · On-site

$51.25 - $69.75/hr

Test Environment, Test Data, Test Cases and Test Scripts etc.) Need a Sr resource - 12-14yrs ... Can we use Freelancer? : No * Named Job Posting? (if Yes - needs to be approved by SCSC) : No

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Freelance Data Engineering information

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$14

$47

$130

How much do freelance data engineering jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for freelance data engineering in California is $47.08, according to ZipRecruiter salary data. Most workers in this role earn between $23.94 and $60.96 per hour, depending on experience, location, and employer.

What is freelance data engineering?

A Freelance Data Engineering job involves designing, building, and maintaining data infrastructure on a contract basis. Freelancers work with businesses to develop ETL pipelines, optimize databases, and manage big data technologies. They often use tools like SQL, Python, Apache Spark, and cloud platforms such as AWS, Google Cloud, or Azure. This role requires strong problem-solving skills and the ability to work independently on data-related projects.

What are the key skills and qualifications needed to thrive as a freelance data engineer?

To excel as a Freelance Data Engineer, you need strong programming skills (Python, SQL), experience with data architecture, ETL processes, and a solid understanding of cloud platforms such as AWS or Azure. Familiarity with tools like Apache Spark, Hadoop, Airflow, and relevant certifications such as Google Cloud Professional Data Engineer or AWS Certified Data Analytics are highly valued. Exceptional communication, project management skills, and the ability to work independently are crucial soft skills in this freelance capacity. These competencies ensure you can efficiently deliver robust data solutions, manage client expectations, and adapt swiftly to diverse project needs.

What are some common challenges faced by freelance data engineers, and how can they be addressed?

Freelance data engineers often face challenges such as managing multiple clients with varying needs, keeping up-to-date with rapidly evolving technologies, and ensuring clear communication despite remote arrangements. To address these challenges, it's important to set clear project expectations from the start, maintain a consistent schedule for learning and skill development, and utilize collaboration tools for effective communication. Building a strong portfolio and leveraging professional networking can also yield steady work opportunities and referrals. Proactively addressing these areas helps freelance data engineers remain competitive and successful in the industry.

What are the most commonly searched types of Data Engineering jobs in California?

The most popular types of Data Engineering jobs in California are:

What are popular job titles related to Freelance Data Engineering jobs in California?

For Freelance Data Engineering jobs in California, the most frequently searched job titles are:

What job categories do people searching Freelance Data Engineering jobs in California look for?

The top searched job categories for Freelance Data Engineering jobs in California are:

What cities in California are hiring for Freelance Data Engineering jobs?

Cities in California with the most Freelance Data Engineering job openings:

Freelance Data Engineering jobs near you
Infographic showing various Freelance Data Engineering job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $97,931 per year, or $47.1 per hour.

Staff Software Engineer, AI Data Platform

Labelbox

San Francisco, CA • On-site

Full-time

Re-posted 28 days ago

Job description

Role Overview

Labelbox is the RL data factory for advancing frontier agent capabilities. We build the data, evaluations, and infrastructure that frontier labs use to train and judge their agents. We're looking for talented, experienced engineers to join us. The bar is high: engineers who have strong judgment and set technical direction, quickly build prototypes that scale into the reliable systems, and are at the frontier of agent-first engineering practices and innovating to accelerate the speed of the business.

What you may work on
  • Eval systems that run millions of agent trajectories to measure model and product quality.
  • Fine-tuning pipelines that turn evaluation signals into measurable agent improvements.
  • Agent-first product surfaces: UX and infrastructure for workflows where the user is a model or an agent operator.
  • The systems behind hundreds of thousands of AI interviews used to source and match freelance workers to projects.
  • Infrastructure that scales to the throughput frontier labs actually need.
  • Integration of the latest models and capabilities into production within days of release.
What we're looking for
  • 4+ year track record of shipping systems customers and other engineers rely on
  • You build full stack prototypes fast and they hold up. The v1 you ship becomes the foundation the rest of the team builds on.
  • Strong system and API design judgement
  • Hard architecture and product calls land with you. You make them, defend them under pressure, and update fast when someone else is right.
  • You ship production code with coding agents daily. You know where they break and what it takes to make them reliable to further accelerate the team's velocity.
  • You set direction by being the example. Other engineers reach for your designs and your code as the reference.
  • You move fast in ambiguous, startup-pace environments with influence over authority.
  • You have worked in all parts of the stack
  • Deep proficiency in TypeScript and/or Python.
Nice to have
  • Production experience building LLM- or agent-driven products.
  • Designing evaluations for LLMs and agents, or producing high-quality data for ML systems.
  • Background in production distributed systems, ML infrastructure, or data systems at scale.
Our Technology Stack

Our engineering team works with a modern tech stack designed for scalability, performance, and developer efficiency:

  • Frontend: React.js with Redux, TypeScript
  • Backend: Node.js, TypeScript, Python, some Java & Kotlin
  • APIs: GraphQL
  • Cloud & Infrastructure: Google Cloud Platform (GCP), Kubernetes
  • Databases: MySQL, Spanner, PostgreSQL
  • Queueing / Streaming: Kafka, PubSub

Apply